Courses

  • Summer 2021

    All Terms Offered

    • Fall 2021

    Official Description

    The application of regression methods to problems in agriculture and natural resources. Topics include simple linear, multiple linear, and nonlinear regression analysis and correlation analysis. Emphasis is placed on predictor variable selection, diagnostics and remedial measures and validation. Both quantitative and qualitative predictor variables are examined. The SAS system is used for all analyses. Course Information: Same as ANSC 541. Prerequisite: CPSC 440 or equivalent.

    TitleSectionCRNTypeHoursTimesDaysLocationInstructor
    Regression AnalysisAB146816LAB003:00 PM - 04:50 PM F  M205 Turner Hall Elhan Ersoz
    Regression AnalysisAB246817LAB001:00 PM - 02:50 PM F  M205 Turner Hall Elhan Ersoz
    Regression AnalysisAL146809LEC502:00 PM - 03:50 PM M W  W223 Turner Hall Elhan Ersoz
  • Fall 2021

    All Terms Offered

    • Fall 2021

    Official Description

    The application of regression methods to problems in the agricultural, biological, and life sciences. Topics include simple linear, multiple linear, nonlinear, and logistic regression analysis and correlation analysis. Emphasis is placed on predictor variable selection, diagnostics, model selection and validation, and remedial measures, including ridge regression, weighted least squares regression, and the use of autoregressive models. Both quantitative and qualitative predictor variables are examined. SAS and R will be used. Course Information: Same as ANSC 541. 5 graduate hours. No professional credit. Prerequisite: CPSC 440 or equivalent.

    TitleSectionCRNTypeHoursTimesDaysLocationInstructor
    Regression AnalysisAB146816LAB003:00 PM - 04:50 PM F  M205 Turner Hall Hamze Dokoohaki
    Regression AnalysisAB246817LAB001:00 PM - 02:50 PM F  M205 Turner Hall Hamze Dokoohaki
    Regression AnalysisAL146809LEC502:00 PM - 03:50 PM M W  W121 Turner Hall Hamze Dokoohaki
  • Spring 2022

    All Terms Offered

    • Fall 2021

    Official Description

    The application of regression methods to problems in the agricultural, biological, and life sciences. Topics include simple linear, multiple linear, nonlinear, and logistic regression analysis and correlation analysis. Emphasis is placed on predictor variable selection, diagnostics, model selection and validation, and remedial measures, including ridge regression, weighted least squares regression, and the use of autoregressive models. Both quantitative and qualitative predictor variables are examined. SAS and R will be used. Course Information: Same as ANSC 541. 5 graduate hours. No professional credit. Prerequisite: CPSC 440 or equivalent.

    TitleSectionCRNTypeHoursTimesDaysLocationInstructor
    Regression AnalysisAB146816LAB003:00 PM - 04:50 PM F  M205 Turner Hall Hamze Dokoohaki
    Regression AnalysisAB246817LAB001:00 PM - 02:50 PM F  M205 Turner Hall Hamze Dokoohaki
    Regression AnalysisAL146809LEC502:00 PM - 03:50 PM M W  W121 Turner Hall Hamze Dokoohaki